Complex Interconnect Structures Research Articles

Defect-rich N, S Co-doped porous carbon with hierarchical channel network for ultrafast capacitive deionization

Developing an eco-friendly and effective approach for preparing N, S co-doped hierarchical porous carbons (NSHPC) for capacitive deionization (CDI) is a huge task for desalination. Herein, NSHPCSKK with interconnected hierarchical pore structures, manufactured via self-activation/co-activation of sodium lignosulfonate (SLS) encapsulation using KNO3-KHCO3 activators, inducing N, S co-doping. Different from NSHPCS and NSHPCSK, NSHPCSKK exhibits the highest specific surface area (SBET, 2264.67 m2/g) and a unique hierarchical pore structure (mesoporous volume/pore volume (Vmeso/ Vpore), 0.65). Small-angle X-ray scattering (SAXS) and scanning electron microscopy (SEM) both reveal the complex interconnected pore structure of NSHPCSKK. Regional Raman imaging conjugated with XPS reveals the presence of extensively distributed N, S co-doped defect structures, providing NSHPCSKK with excellent wettability and electrochemical performance. DFT calculations indicate that the N, S co-doping at the defect sites depicts excellent adsorption capability. Eventually, NSHPCSKK acquired an impressive salt adsorption capacity (SAC) of 20.5 mg/g and the highest average salt adsorption rate (ASAR) of 12.1 mg/g/min, indicating its superior desalting performance. In-situ Raman spectroscopy confirms NSHPCSKK’s rapid ion regeneration mechanism. The research introduces a span-new NSHPC synthesis strategy for fabricating advanced NSHPC with rapid desalination response for upgrading CDI desalination.

Optimization of the 3D multi-level SOT-MRAMs

With the development of electronic technology, semiconductor memory is gradually shifting toward smaller area with less power consumption. SOT-MRAM is one of the competitive substitutes for DRAM and SRAM due to its superior endurance and switching speed. In contrast to STT-MRAM, the separation of read and write routes allows SOT-MRAM to have a lower error rate and higher lifetime, but this comes at the expense of the memory density. In recent years, vertical integrated circuits have relied on TSV to complete 3D stacking to ease the pressure of Moore's Law on scaling circuits. SOT-MRAM can take advantage of 3D stacking to reduce power and latency. More importantly, the density of SOT-MRAM can be improved at the same time. In the paper, simulation is conducted based on DESTINY, with the TSV model supplemented to NVSIM to evaluate the performance of MRAM 3D structures. The 3D SOT-MRAM structure in DESTINY can be implemented with a bus layer and interconnect structure between layers, which greatly reduces the expense of area. However, the 3D structure requires a more complex interconnect structure to truly meet the requirements of high density. For this reason, 3D model of unit interconnection using TSV is presented in the paper. Memory has several components, of which the memory array is the one with the largest area share. This paper explores the spatial structure of the array and proposes a new model which allows more complex interconnect structures to be accomplished on the same area.

Disruption of Leishmania flagellum attachment zone architecture causes flagellum loss.

Leishmania are flagellated eukaryotic parasites that cause leishmaniasis and are closely related to the other kinetoplastid parasites such as Trypanosoma brucei. In all these parasites there is a cell membrane invagination at the base of the flagellum called the flagellar pocket, which is tightly associated with and sculpted by cytoskeletal structures including the flagellum attachment zone (FAZ). The FAZ is a complex interconnected structure linking the flagellum to the cell body and has critical roles in cell morphogenesis, function and pathogenicity. However, this structure varies dramatically in size and organisation between these different parasites, suggesting changes in protein localisation and function. Here, we screened the localisation and function of the Leishmania orthologues of T. brucei FAZ proteins identified in the genome-wide protein tagging project TrypTag. We identified 27 FAZ proteins and our deletion analysis showed that deletion of two FAZ proteins in the flagellum, FAZ27 and FAZ34 resulted in a reduction in cell body size, and flagellum loss in some cells. Furthermore, after null mutant generation, we observed distinct and reproducible changes to cell shape, demonstrating the ability of the parasite to adapt to morphological perturbations resulting from gene deletion. This process of adaptation has important implications for the study of Leishmania mutants.

Magneto-transport behavior of disordered three dimensional NixCo1−x inverse opal networks

Herein we report on the magneto-transport properties of disordered three dimensional inverse opals (3D-IOs) fabricated by a standard three-probe electrodeposition technique into the interstices of porous membranes made of 150 nm diameter self assembled poly(methyl methacrylate) spheres. This approach has allowed the synthesis of large scale nanocomposites with exact ferromagnetic NixCo1−x alloy compositions and complex interconnected structure. Particularly, the microstructure of Co-rich 3D-IOs is consistent with the hexagonal close packed hcp texture and its corresponding magnetoresistance is explained in terms of the hcp Co magnetocrystalline anisotropy contribution. Conversely, the magnetoresistive behavior of Ni-rich 3D-IO networks is explained in terms of only their magnetostatic field. The control of these features is made possible by the reduced dimensions of necks and walls, in the 40 nm to 60 nm range, of the 3D-IO structure. Despite the disordered morphology of these 3D-IO nanoarchitectures, their microstructural and magneto-transport properties can be fine tuned due to the reduced nanoscale dimensions of the electrical interconnections. These properties have been found to be comparable to those obtained in other 3D networks, making them interesting systems for their potential use for magnetic sensing and spintronic applications.

The political economy of big data leaks: Uncovering the skeleton of tax evasion

After the leak of 11.5 million documents from the Panamanian corporation Mossack Fonseca, an intricate network of offshore business entities has been revealed. The emerging picture is that of legal entities, either individuals or companies, involved in offshore activities and transactions with several tax havens simultaneously which establish, indirectly, an effective network of countries acting on tax evasion. The analysis of this network quantitatively uncovers a strongly connected core (a rich-club) of countries whose indirect interactions, mediated by legal entities, form the skeleton for tax evasion worldwide. Intriguingly, the rich-club mainly consists of well-known tax havens such as British Virgin Islands and Hong Kong, and major global powers such as China, Russia, United Kingdom and United States of America. Our findings build a ground for better understanding phenomena where the erosion of public trust may spark emergent social dynamics, such as social conflicts and political polarization, that are driven by the complex interconnected structure of tax evaders in a globalized economy.

CacheEM: For Reliability Analysis on Cache Memory Aging Due to Electromigration

Electromigration (EM) is crucial for interconnect reliability. This article introduces the implementation and application of CacheEM which targets SRAM cache memory aging due to EM. CacheEM is based on a comprehensive framework including five parts: 1) microprocessor emulation; 2) memory cell array activity extraction; 3) computation of currents in segments of long complex interconnect structures; 4) evaluation of the time-dependent hydrostatic stress and the resistance shift of interconnects; and 5) characterization of the EM lifetime distribution of interconnects in the cache memory. The first two steps (top-down) are implemented with gem5 and cache simulation, respectively. These simulators export the number of read and write operations for each cell of a cache memory in a microprocessor after running benchmarks. Then, based on the number of operations and the currents corresponding to each operation, CacheEM calculates the equivalent current distribution in each interconnect segment as the third step (bottom-up). The currents due to read and write operations are stored in models which have been pretrained with a regression algorithm. These models provide accurate predictions of the corresponding currents under various parameter settings, such as temperature, supply voltage, and gate length. Afterward, the samples of time-dependent hydrostatic stress and the resistance shift in each interconnect segment are computed while incorporating the variations of the effective activation energy and critical stress. The EM lifetime distribution of the cache memory is extracted using predefined threshold values. The impact of configuration parameters on EM reliability and performance of the SRAM cache is analyzed by comparing EM lifetime distributions.

Influence of model inclination on the melting behavior of graded metal foam composite phase change material: A pore-scale study

Metal foam has been widely employed to accelerate the melting behavior of latent heat thermal energy storage (LHTES) system. Nevertheless, its homogeneous structure has a limited enhancement on the conductive and convective heat transfers in the melting process. In this study, we numerically studied the heat storage performance of the graded metal foam composite phase change materials (CPCMs). The body-centered-cubic unit was conducted to represent the metal foam with a complex interconnected structure. For clarifying the effect of heat flux orientation, we built seven models with the inclinations of 0˚, 30˚, 60˚, 90˚, 120˚, 150˚, 180˚, respectively. Meanwhile, three types of metal foams with different structures, including the uniform, negative, and positive porosities, were built to enhance the melting process and analyze their effects. By comparing the melting performances of the uniform models with different inclinations, it is found that the heat flux orientations (model inclinations) have significant impacts on the melting behaviors. The models with large inclinations (θ > 90˚) have faster melting-processes compared with those small inclinations (θ ≤ 90˚). Besides, by comparing the models with different graded structures, we conclude that the negative model is the most helpful to the charging process. When the inclinations of the models are 120˚ and 150˚, the negative models have reductions of 11.06% on the complete melting times compared with those uniform models. Nevertheless, the models with small inclinations were slightly enhanced by negative porosity structure (0.52%–3.15%) but significantly weakened by positive structure (21.93%–30.00%). The study reveals the effects of heat flux orientation and graded metal foam on the melting performance of PCM. It provides a design and optimized reference for the models with tilted angles such as electronic devices and plate latent heat storage systems.

Volitional control of individual neurons in the human brain.

Brain-machine interfaces allow neuroscientists to causally link specific neural activity patterns to a particular behaviour. Thus, in addition to their current clinical applications, brain-machine interfaces can also be used as a tool to investigate neural mechanisms of learning and plasticity in the brain. Decades of research using such brain-machine interfaces have shown that animals (non-human primates and rodents) can be operantly conditioned to self-regulate neural activity in various motor-related structures of the brain. Here, we ask whether the human brain, a complex interconnected structure of over 80 billion neurons, can learn to control itself at the most elemental scale-a single neuron. We used the unique opportunity to record single units in 11 individuals with epilepsy to explore whether the firing rate of a single (direct) neuron in limbic and other memory-related brain structures can be brought under volitional control. To do this, we developed a visual neurofeedback task in which participants were trained to move a block on a screen by modulating the activity of an arbitrarily selected neuron from their brain. Remarkably, participants were able to volitionally modulate the firing rate of the direct neuron in these previously uninvestigated structures. We found that a subset of participants (learners), were able to improve their performance within a single training session. Successful learning was characterized by (i) highly specific modulation of the direct neuron (demonstrated by significantly increased firing rates and burst frequency); (ii) a simultaneous decorrelation of the activity of the direct neuron from the neighbouring neurons; and (iii) robust phase-locking of the direct neuron to local alpha/beta-frequency oscillations, which may provide some insights in to the potential neural mechanisms that facilitate this type of learning. Volitional control of neuronal activity in mnemonic structures may provide new ways of probing the function and plasticity of human memory without exogenous stimulation. Furthermore, self-regulation of neural activity in these brain regions may provide an avenue for the development of novel neuroprosthetics for the treatment of neurological conditions that are commonly associated with pathological activity in these brain structures, such as medically refractory epilepsy.

A correction method for the ambient temperature-induced error in hydrostatic leveling systems and application

In an HLS, the error come from many factors, among which temperature may be one of the most important factors. If the ambient temperature changes, the liquid level in the liquid storage tank and the water level at all the points for placement of sensors will change. However, due to the complex interconnection structure of HLS, the change of the liquid level at the reference measurement point and that at the other monitoring points are not the same, resulting in ambient temperature induced error, which can be calculated according to the theoretical formula. This error can be eliminated effectively by using the correction method for ambient temperature induced error in hydrostatic leveling systems. When this part of error is eliminated, the error of the monitoring points is reduced. At last, the method was used in the Gongchangling open-pit iron mine to reveal the variation characteristic of surface settlement above goaf.

Identification of Logic Paths Influenced by Severe Coupling Capacitances

Signals in modern integrated circuits travel through complex interconnect structures, which present several layers and important coupling capacitance effects. Even more, the impact of signal coupling on the overall circuit behavior has grown with technology scaling as the interconnect have become taller. In this paper, a methodology to identify those logic paths more significantly influenced by the coupling capacitances is presented. The proposed methodology is based on a modified Dijkstra’s algorithm, which finds those paths between a primary input and a primary output more severely influenced by the coupling capacitances. This methodology can be used to validate circuit behavior and it can also be applied in testing techniques oriented to detect interconnect defects (e.g., opens and short defects). The proposed methodology is applied to ISCAS’85 benchmark circuits to show its feasibility.

Distributed Resource Allocation Over Dynamic Networks With Uncertainty

Motivated by broad applications in various fields of engineering, we study a network resource allocation problem where the goal is to optimally allocate a fixed quantity of the resources over a network of nodes. We consider large scale networks with complex interconnection structures, thus any solution must be implemented in parallel and based only on local data resulting in a need for distributed algorithms. In this article, we study a distributed Lagrangian method for such problems. By utilizing the so-called distributed subgradient methods to solve the dual problem, our approach eliminates the need for central coordination in updating the dual variables, which is often required in classic Lagrangian methods. Our focus is to understand the performance of this distributed algorithm when the number of resources is unknown and may be time-varying. In particular, we obtain an upper bound on the convergence rate of the algorithm to the optimal value, in expectation, as a function of network topology. The effectiveness of the proposed method is demonstrated by its application to the economic dispatch problem in power systems, with simulations completed on the benchmark IEEE-14 and IEEE-118 bus test systems.

Broadband Circuit Model for EMI Analysis of Complex Interconnection Networks in Metallic Enclosures of Arbitrary Shape

In this article, a broadband equivalent circuit was developed to model the electromagnetic behavior of complex interconnection structures in metallic casings of arbitrary geometry. Based on the eigenfunctions of the system, this model is inherently stable in the time domain due to its passivity and allows simulation by a commercial circuit simulator with arbitrary linear or nonlinear port terminations. The typically slow convergence of the circuit model is accelerated by the extraction of quasi-static inductances and capacitances and losses are considered by additional resistive elements. The presented model is validated in the frequency domain by elaborate full-wave simulations.

Novel design of low modulus high strength zirconia scaffolds for biomedical applications

This study intends to develop a novel zirconia scaffold design with a significantly lower Young's Modulus than zirconia bulk material (210 GPa) aiming to match this elastic property with that of the host bone, for application as endosseous implants. This scaffold with a complex interconnected structure can allow bone ingrowth, vascularization and provide a good initial stability. This novel thin-walled zirconia scaffold was manufactured by green machining and afterwards furnace sintered. The obtained YM of this zirconia scaffold was found significantly lower than zirconia bulk material due a less stiff geometry with small (walls and floors) dimensions. Insertion replication tests were performed for evaluating the fixation at the initial moment of implantation, being experimentally verified a high static initial coefficient of friction. The capillarity of these scaffolds was also assessed, revealing a very high rising speed of water inside these structures. This study proved that this novel ceramic scaffold design can be fabricated for several dimensions for obtaining desired elastic properties. The proposed fabrication strategy allows the fabrication of thin-walled structures unachievable by conventional machining.

Governing Competition and Collaboration in Network Industries Using Agent-Based Modeling: A Case-Study of US Air Transportation Network

Network industries include a multitude of organizations and companies delivering valuable services and products for modern life. Surprisingly, the impact of the structural complexity of their underlying physical infrastructure on the behavior of these organizations has not been explored yet. The aim of this paper is to study the role of an initial network structure on the throughput of these complex systems, and to provide evidence for the value of using agent-based modeling (ABM) in governing competition and collaboration in network industries. A two-stage multiround game provides the mathematical foundation to examine the behavior of players in the complex interconnected structure of a network industry. The United States Air Transportation Network is used as the case study. The real data on the different elements of the system are embedded into an agent-based model to provide a descriptive model of behaviors within it. The outcome of the model shows path dependence in the system and highlights the impact of initial network conditions on the market. Moreover, this model provides evidence on the usefulness of ABM for understanding the interrelationships between economic behavior and the physical structure of the system.

A hybrid SD-DEMATEL approach to develop a delay model for construction projects

PurposeThe purpose of this paper is to develop a model for complex interconnected structure of various factors interacting with delay in order to identify the most important factors influencing and influenced by delay based on their interrelations.Design/methodology/approachReviewing literature and interviewing with local experts selected from the Iranian construction industry, top 58 delay factors were identified and categorized into six major groups. The interrelations among these factors were, then, modeled using the system dynamics (SD) approach. The resulting causal loop diagrams obtained from SD were used subsequently for identifying the most significant factors influencing and influenced by delay through the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The impact of factors on each other was finally determined based on the opinions of 63 experts selected from the Iranian community of consultants, contractors, and clients.FindingsAccording to the analysis, eight out of the 58 factors were identified as the most influencing factors on delay, and nine factors were found to be the most influenced factors by delay in the field of delay analysis. The study also concluded that factors related to labors are the most important and influential factors. In addition, factors related to client were the most influencing factors and external-related factors were the least important ones. At the end, some recommendations to reduce variation of delay in the construction projects are presented as well.Originality/valueConsidering the interconnected structure of the factors, the paper identifies the most important factors interacting with time delay in construction projects.

Test of Mechanical Failure for Via Holes and Solder Joints of Complex Interconnect Structure

It is known that certain faults associated with the process might be generated in any phases of the fabrication and assembly of the complex interconnection structure in a high-speed PCB composed of via holes, solder joints and traces, which will inevitably discount the electrical performance of the circuit. To address the issue, a fault-voltage detection method is proposed in this paper, firstly the equivalent fault circuit of the complex interconnection structure in high-speed PCB is scanned to extract the fault voltage, then the optimal function curve can be fitted out by the least squares method based on the faultless voltage. The empirical research on the via hole crack and solder joint void have validated that this method can effectively avoid the false tests derived under the low-frequency, major-fault and high-frequency, minor-fault conditions, and can also depict more accurately how the fault parameter varies with the changes in the frequency and fault degree, and it bears a relatively strong applicability in minor-fault of hiht-speed PCB tests.

Orthotropic elastic constants of 2D cellular structures with variously arranged square cells: The effect of filleted wall junctions

Cellular materials are characterized by a complex interconnected structure of struts or plates and shells, which make up the cells edges and faces. Their structure can be advantageously engineered in order to tailor their properties according to the specific application. This aspect makes them particularly attractive for the manufacturing of bone prosthetics, where the elastic modulus of the implant should match that of the bone in order to avoid loosening due to the stress shielding phenomenon. In this regard, the ability to design a component with the desired mechanical response is crucial. For this reason, the present paper evaluates the stiffness of 2D cellular structures with variously arranged square cells. Specifically, two spatial arrangements are considered: the former one is a regular square cell honeycomb, while in the latter the square cells are staggered by a prescribed offset of half of the cell wall length. An analytical model based on classical beam theory is proposed to identify the effect of stretching and bending actions on the stiffness of a single cell by applying the periodic boundary conditions. The theoretical beam model is fitted on the results from a 2D Finite Elements model based on plane elements via an extensive parametric analysis. In this way, semi-analytical formulas are proposed to calculate the stiffness in large domains of the geometric parameters: wall thickness to edge length ratio in the interval [0.04,0.20] and fillet radius to edge length ratio in the interval [0,0.15].

Identification of dynamic models in complex networks with prediction error methods—Basic methods for consistent module estimates

The problem of identifying dynamical models on the basis of measurement data is usually considered in a classical open-loop or closed-loop setting. In this paper, this problem is generalized to dynamical systems that operate in a complex interconnection structure and the objective is to consistently identify the dynamics of a particular module in the network. For a known interconnection structure it is shown that the classical prediction error methods for closed-loop identification can be generalized to provide consistent model estimates, under specified experimental circumstances. Two classes of methods considered in this paper are the direct method and the joint-IO method that rely on consistent noise models, and indirect methods that rely on external excitation signals like two-stage and IV methods. Graph theoretical tools are presented to verify the topological conditions under which the several methods lead to consistent module estimates.

Multifractal analysis of earthquakes in Kumaun Himalaya and its surrounding region

Himalayan seismicity is related to continuing northward convergence of Indian plate against Eurasian plate. Earthquakes in this region are mainly caused due to release of elastic strain energy. The Himalayan region can be attributed to highly complex geodynamic process and therefore is best suited for multifractal seismicity analysis. Fractal analysis of earthquakes (mb ≥ 3.5) occurred during 1973–2008 led to the detection of a clustering pattern in the narrow time span. This clustering was identified in three windows of 50 events each having low spatial correlation fractal dimension (D C ) value 0.836, 0.946 and 0.285 which were mainly during the span of 1998 to 2005. This clustering may be considered as an indication of a highly stressed region. The Guttenberg Richter b-value was determined for the same subsets considered for the D C estimation. Based on the fractal clustering pattern of events, we conclude that the clustered events are indicative of a highly stressed region of weak zone from where the rupture propagation eventually may nucleate as a strong earthquake. Multifractal analysis gave some understanding of the heterogeneity of fractal structure of the seismicity and existence of complex interconnected structure of the Himalayan thrust systems. The present analysis indicates an impending strong earthquake, which might help in better hazard mitigation for the Kumaun Himalaya and its surrounding region.

A Thermal Simulation Process Based on Electrical Modeling for Complex Interconnect, Packaging, and 3DI Structures

To reduce the product development time and achieve first-pass silicon success, fast and accurate estimation of very-large-scale integration (VLSI) interconnect, packaging and 3DI (3D integrated circuits) thermal profiles has become important. Present commercial thermal analysis tools are incapable of handling very complex structures and have integration difficulties with existing design flows. Many analytical thermal models, which could provide fast estimates, are either too specific or oversimplified. This paper highlights a methodology, which exploits electrical resistance solvers for thermal simulation, to allow acquisition of thermal profiles of complex structures with good accuracy and reasonable computation cost. Moreover, a novel accurate closed-form thermal model is developed. The model allows an isotropic or anisotropic equivalent medium to replace the noncritical back-end-of-line (BEOL) regions so that the simulation complexity is dramatically reduced. Using these techniques, this paper introduces the thermal modeling of practical complex VLSI structures to facilitate thermal guideline generation. It also demonstrates the benefits of the proposed anisotropic equivalent medium approximation for real VLSI structures in terms of the accuracy and computational cost.